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2017 December 24

Choosing a grad school

Filed under: Uncategorized — gasstationwithoutpumps @ 11:56
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One of my more popular posts has been Where you get your BS in CS matters, which looked at a report on which universities sent students on to PhD programs in computer science.  Choosing a college for undergraduate studies based on reputation or rankings is always problematic, because the ratings generally measure the wrong thing (usually size, wealth, and reputation, rather than educational quality).

Choosing a grad school is also difficult.  Reputation for research quality matters more for choosing a grad school than for an undergraduate, because grad students are expected to do research and their future careers may be highly affected by the reputation of their advisers or grad schools.  But overall reputation is not enough—reputation within a subfield is what matters most.

An important question for students applying to grad schools to ask is whether the places they are applying to (or are accepted at) will provide a rich environment for the sort of research they want to do.

When I was applying to grad schools (44 years ago), I made the mistake of looking only at overall reputation, and chose the math department at Stanford. The first year in math grad programs consisted of three subjects: real analysis, complex analysis, and abstract algebra (I believe that math grad program have not changed this focus in the past 4 decades).  After I passed my comprehensive exams (3 grueling 6-hour exams), I started looking for a thesis topic and an adviser and realized that no one in Stanford’s math department at the time did the sort of math I enjoyed (discrete math: combinatorics and graph theory).  Luckily, Stanford’s computer science department had four faculty in those fields, and the CS department there accepted my application for a transfer.  As it turned out, I didn’t end up doing combinatorics, graph theory, or any of the mathematical computer science subfields—I flirted with a lot of subjects (including computer music) and my thesis was in computer-aided design for VLSI.

Grad school applicants nowadays don’t have to make my mistake—they have access to much more information and much finer-grained information about grad programs than was easily available 40 years ago.  One resource worth looking at is CS Rankings, which ranks computer science programs based on publications in some of the top conferences in computer science.  In addition to the raw rankings (which can be highly misleading), the website also provides pie charts that give the breakdown of the publications by field.

For example, UC Berkeley is ranked top of the UC system and the pie chart shows particular strength in robotics, vision, and machine learning.  UC Santa Barbara is ranked as number 26, with particular strengths in security, databases, and electronic design automation (EDA).

But the particular method used is problematic, because of the reliance on a small number of conferences.  For example, UCSC’s strength in bioinformatics is not visible, because most of the publications are in biology journals (and glam journals like Nature), not in the two conferences that the rankings use (RECOMB and ISMB).  Conference publications are the main coin of the realm in most of CS, but not in bioinformatics, where journal publications rule. UCSC’s strength in storage systems is also not well represented, because FAST and USENIX ATC (two of the major conferences in that field) are not included.

The CSRankings.org method has some weird artifacts (like rewarding short author lists that exclude students and postdocs) and can be gamed in various ways.  Indeed, the ranking of institutions has changed enormously in the last two weeks, as departments have scrambled to up their averages by including affiliated faculty with high weighted publication counts and exclude those with low ones.

Despite the rather serious limitations of the CSrankings.org method, it is a more informative and useful system for comparing grad schools than ones like US News and World Report’s, which seem to bear almost no relationship with reality, being based almost entirely on hearsay reputation.

The best thing to use the CSRankings for is to look for what fields an institution is strong in (keeping in mind that many fields are not properly represented by the selection of conferences) and what faculty are publishing highly in the conferences that the CSRankings organizers think are important.  Grad school applicants should follow up by looking at the web pages of the faculty in the subfields that interest them (and check to make sure that the faculty are still there—people move around and a strong subfield 5 years ago may be missing now as faculty moved to industry or other academic positions).

2 Comments »

  1. I like my method much better. It was close, had a decent program and best of all, they were willing to hire me to teach while I was working on my degree. Food and rent ! Yippee!

    Comment by gflint — 2017 December 26 @ 09:08 | Reply

    • Most STEM programs pay stipends for PhD students (though not MS students), so price is generally not a determining factor in choosing a PhD program. In recent years the cost of rent has gone up faster than grad stipends, though, so one does have to be a bit careful in the more expensive housing markets (which coincide with some of the best schools) to make sure that the grad stipend is enough to cover rent, food, and health insurance.

      MS programs are still seen by universities as cash cows—and MS degree in engineering is still a good investment, but it costs a lot. MS students should focus on finishing the degrees quickly, which means that they should start the MS programs with a good idea what courses they will take and what they will get out of the program.

      Comment by gasstationwithoutpumps — 2017 December 26 @ 09:33 | Reply


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